Nonparametric regression estimation under mixing conditions

[1]  J. Doob.  Stochastic processes , 1953 .

[2]  G. Roussas.  Nonparametric Estimation of the Transition Distribution Function of a Markov Process , 1969 .

[3]  I. Ibragimov,et al.  Independent and stationary sequences of random variables , 1971 .

[4]  B. Silverman,et al.  Weak and strong uniform consistency of kernel regression estimates , 1982 .

[5]  P. Robinson.  NONPARAMETRIC ESTIMATORS FOR TIME SERIES , 1983 .

[6]  P. Robinson.  Robust Nonparametric Autoregression , 1984 .

[7]  W. Härdle.  Robust regression function estimation , 1984 .

[8]  W. Härdle,et al.  Uniform Consistency of a Class of Regression Function Estimators , 1984 .

[9]  G. Collomb.  Propriétés de convergence presque complète du prédicteur à noyau , 1984 .

[10]  G. Collomb.  Jfon parametric time series analysis and prediction: uniform almost sure convergence of the window and jt-nn autoregression estimates , 1985 .

[11]  P. Robinson,et al.  On the consistency and finite-sample properties of nonparametric kernel time series regression, autoregression and density estimators , 1986 .

[12]  Wolfgang Härdle,et al.  SOME THEORY ON M‐SMOOTHING OF TIME SERIES , 1986 .

[13]  Wolfgang Härdle,et al.  Strong Uniform Convergence Rates in Robust Nonparametric Time Series Analysis and Prediction: Kernel , 1986 .

[14]  George G. Roussas,et al.  Moment inequalities for mixing sequences of random variables , 1987 .

[15]  S. Yakowitz.  NEAREST‐NEIGHBOUR METHODS FOR TIME SERIES ANALYSIS , 1987 .

[16]  G. Roussas.  Nonparametric estimation in mixing sequences of random variables , 1988 .